Quantifying collective intelligence in human groups

Area of Science:

• Social Psychology
• Organizational Behavior
• Group Dynamics

Background:

• Collective intelligence (CI) is crucial for addressing complex challenges in science and business.
• Groups frequently underperform, failing to reach their full collective potential.
• Understanding the factors that predict and enhance group CI is essential.

Purpose of the Study:

• To identify key predictors of collective intelligence (CI) across diverse group tasks.
• To investigate the role of group composition, specifically gender diversity, in CI.
• To determine whether group processes or individual skills are more influential for CI.

Main Methods:

• Analysis of group performance data from 22 studies, encompassing 5,279 individuals in 1,356 groups.
• Statistical modeling to identify factors predicting CI and its impact on performance.
• Examination of mediation effects, such as social perceptiveness, in the relationship between group composition and CI.

Main Results:

• A robust collective intelligence factor was identified, demonstrating a group's general ability to collaborate effectively.
• The proportion of women in a group significantly predicted CI, mediated by members' average social perceptiveness.
• Group collaboration processes were found to be more critical for predicting CI than individual member skills.

Conclusions:

• Collective intelligence is a measurable group-level trait influenced by diversity and social dynamics.
• Enhancing group composition (e.g., gender diversity) and collaboration processes can improve collective intelligence.
• Focusing on group dynamics and social perceptiveness offers a promising avenue for boosting group performance and problem-solving capabilities.